How Do Trainees Rate the Impact of a Short Cognitive Behavioural Training Programme on their Knowledge and Skills?

Background: A strong evidence base for cognitive behavioural therapy has led to CBT models becoming available within mainstream mental health services. As the concept of stepped care develops, new less intensive mental health interventions such as guided self-help are emerging, delivered by staff not trained to the level of accredited Cognitive Behavioural Therapists. Aim: The aim of this study was to determine how mental health staff evaluated the usefulness of a short training programme in CBT concepts, models and techniques for routine clinical practice.
Method: A cohort of mental health staff (n = 102) completed pre- and posttraining self-report questionnaires measuring trainee perceptions of the impact of a short training programme on knowledge and skills. Mentors and managers were also asked to comment on perceived impact of the training.
Results: Trainees and mentors reported perceived gains in knowledge and skills posttraining and at 1-year follow-up. Managers and trainees reported perceived improvements in skills and practice. Conclusion: A short Cognitive Behavioural skills programme can enable mental health staff to integrate basic CB knowledge and skills into routine clinical practice.

The ParaPhrase Project:Parallel patterns for adaptive heterogeneous multicore systems

This paper describes the ParaPhrase project, a new 3-year targeted research project funded under EU Framework 7 Objective 3.4 (Computer Systems), starting in October 2011. ParaPhrase aims to follow a new approach to introducing parallelism using advanced refactoring techniques coupled with high-level parallel design patterns. The refactoring approach will use these design patterns to restructure programs defined as networks of software components into other forms that are more suited to parallel execution. The programmer will be aided by high-level cost information that will be integrated into the refactoring tools. The implementation of these patterns will then use a well-understood algorithmic skeleton approach to achieve good parallelism. A key ParaPhrase design goal is that parallel components are intended to match heterogeneous architectures, defined in terms of CPU/GPU combinations, for example. In order to achieve this, the ParaPhrase approach will map components at link time to the available hardware, and will then re-map them during program execution, taking account of multiple applications, changes in hardware resource availability, the desire to reduce communication costs etc. In this way, we aim to develop a new approach to programming that will be able to produce software that can adapt to dynamic changes in the system environment. Moreover, by using a strong component basis for parallelism, we can achieve potentially significant gains in terms of reducing sharing at a high level of abstraction, and so in reducing or even eliminating the costs that are usually associated with cache management, locking, and synchronisation. © 2013 Springer-Verlag Berlin Heidelberg.

Towards utilizing Model-Driven Engineering of Composite Applications for business performance analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

The Development of TASTER, a Cognitive Training Game Using Human-Centered Design, Tailored for Children with Global and Specific Cognitive Impairments

Children with Prader-Willi syndrome often exhibit challenging behavior in response to changes to routine. This phenomenon has been linked to a deficit in task switching ability which has been observed in children with the syndrome. TASTER is a cognitive training game which is being designed with input from a group of children with Prader- Willi syndrome, which aims to train task switching ability and thus reduce associated challenging behavior.

Location decision-making of 'creative' industries: the media and computer games sectors in Dublin, Ireland

There has been significant research undertaken examining the “creative class” thesis within the context of the locational preferences of creative workers. However, relatively little attention has been given to the locational preferences of creative companies within the same context. This paper reports on research conducted to qualitatively analyse the location decision making of companies in two creative sectors: media and computer games. We address the role of the so-called “hard” and “soft” factors in company location decision making within the context of the creative class thesis, which suggests that company location is primarily determined by “soft” factors rather than “hard” factors. The study focuses upon “core” creative industries in the media and computer game sectors and utilises interview data with company managers and key elite actors in the sector to investigate the foregoing questions. The results show that “hard” factors are of primary importance for the location decision making in the sectors analysed, but that “soft” factors play quite an important role when “hard” factors are satisfactory in more than one competing city-region.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.